From 4277fa288712f75e6393901461f82f42b5c46fd3 Mon Sep 17 00:00:00 2001
From: Jonathan Tompson <tompson@cims.nyu.edu>
Date: Thu, 26 Jun 2014 16:49:34 -0400
Subject: removed fprop test for SpatialUpSamplingNearest.

---
 test/test.lua | 40 ----------------------------------------
 1 file changed, 40 deletions(-)

(limited to 'test')

diff --git a/test/test.lua b/test/test.lua
index 7a23c5e..5e4bce7 100644
--- a/test/test.lua
+++ b/test/test.lua
@@ -1907,46 +1907,6 @@ function nntest.SpatialUpSamplingNearest()
     local ferr, berr = jac.testIO(m, input)
     mytester:asserteq(ferr, 0, torch.typename(m)..' - i/o forward err ')
     mytester:asserteq(berr, 0, torch.typename(m)..' - i/o backward err ')
-
-    -- Also check that the forward prop is correct.
-    input = torch.rand(unpack(shape))
-    local output = m:forward(input)
-
-    local feat
-    local nfeats
-    if input:dim() == 3 then
-      nfeats = shape[1]
-      feat = {0}
-    else
-      feat = {0, 0}
-      nfeats = shape[1] * shape[2]
-    end
-    feat[#feat+1] = 0  -- ydim
-    feat[#feat+1] = 0  -- xdim
-    local xdim = input:dim()
-    local ydim = input:dim()-1
-    local err = 0
-    for f = 1, nfeats do
-      if input:dim() == 4 then
-        feat[1] = math.floor((f-1) / shape[1]) + 1
-        feat[2] = math.mod((f-1), shape[2]) + 1
-      else
-        feat[1] = f
-      end
-      for y = 1, input:size(ydim) * scale do
-        for x = 1, input:size(xdim) * scale do
-          feat[ydim] = y
-          feat[xdim] = x
-          local oval = output[feat]
-          feat[ydim] = math.floor((y-1)/scale)+1
-          feat[xdim] = math.floor((x-1)/scale)+1
-          local ival = input[feat] 
-          err = math.max(err, math.abs(oval-ival))
-        end
-      end
-    end
-
-    mytester:assertlt(err, precision, ' fprop is incorrect ')
   end
 end
 
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